Estimating parameters with ensemble-based data assimilation : a review.

• Autores: Ruiz, Juan Jose; Pulido, Manuel Arturo; Miyoshi, Takemasa
• Año de publicación: 2013
• Idioma: inglés
• Tipo de recurso: artículo
• Materia: PARAMETER ESTIMATION; DATA ASSIMILATION; ENSEMBLE KALMAN FILTER
• Institución: Consejo Nacional de Investigaciones Científicas y Técnicas

Weather forecast and earth system models usually have a number of parameters, which are often optimizedmanually by trial and error. Several studies have proposed objective methods to estimate model parameters using dataassimilation techniques. This paper provides a review of the previous studies and illustrates the application ofensemble-based data assimilation to the estimation of temporally varying model parameters in a simple low-resolutionatmospheric general circulation model known as the SPEEDY model. As shown in previous studies, our resultshighlight that data assimilation techniques are efficient optimization methods which can be used for parameterestimation in complex geophysical models and that the estimated parameters have a positive effect on short-tomedium-range numerical weather prediction.
Fil: Ruiz, Juan Jose. Universidad Nacional del Nordeste. Facultad de Ciencias Exactas Naturales y Agrimensura; Argentina; Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Nordeste. Instituto de Modelado e Innovación Tecnológica; Argentina;
Fil: Pulido, Manuel Arturo. Universidad Nacional del Nordeste. Facultad de Ciencias Exactas Naturales y Agrimensura; Argentina; Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Nordeste. Instituto de Modelado e Innovación Tecnológica; Argentina;
Fil: Miyoshi, Takemasa. University of Maryland; Estados Unidos de América;